Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction

Fuente: arXiv
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Main Authors: Tofigh, Mani, Guo, Edward, Jia, Weiwei, Ding, Xiaoning, Zhao, Zirui Neil, Shan, Jianchen
Format: Preprint
Published: 2025
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author Tofigh, Mani
Guo, Edward
Jia, Weiwei
Ding, Xiaoning
Zhao, Zirui Neil
Shan, Jianchen
author_facet Tofigh, Mani
Guo, Edward
Jia, Weiwei
Ding, Xiaoning
Zhao, Zirui Neil
Shan, Jianchen
contents This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs, but a VM is unaware of cache provisioning details. Moreover, a VM cannot influence cache usage via page placement policies, as memory-to-cache mappings are hidden. The paper proposes a novel solution, CacheX, which probes accurate and fine-grained cache abstraction within VMs using eviction sets without requiring hardware or hypervisor support, and showcases the utility of the probed information with two new techniques: LLC contention-aware task scheduling and virtual color-aware page cache management. Our evaluation of CacheX's implementation in x86 Linux kernel demonstrates that it can effectively improve cache utilization for various workloads in public cloud VMs.
format Preprint
id arxiv_https___arxiv_org_abs_2511_09956
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction
Tofigh, Mani
Guo, Edward
Jia, Weiwei
Ding, Xiaoning
Zhao, Zirui Neil
Shan, Jianchen
Distributed, Parallel, and Cluster Computing
Operating Systems
Performance
This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs, but a VM is unaware of cache provisioning details. Moreover, a VM cannot influence cache usage via page placement policies, as memory-to-cache mappings are hidden. The paper proposes a novel solution, CacheX, which probes accurate and fine-grained cache abstraction within VMs using eviction sets without requiring hardware or hypervisor support, and showcases the utility of the probed information with two new techniques: LLC contention-aware task scheduling and virtual color-aware page cache management. Our evaluation of CacheX's implementation in x86 Linux kernel demonstrates that it can effectively improve cache utilization for various workloads in public cloud VMs.
title Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction
topic Distributed, Parallel, and Cluster Computing
Operating Systems
Performance
url https://arxiv.org/abs/2511.09956